---
title: "Income disparity, ranking and number of tax filers across the TN counties from 2011-2015. "
output:
flexdashboard::flex_dashboard:
orientation: rows
social: menu
source_code: embed
---
```{r setup, include=FALSE}
library(flexdashboard)
library(ggplot2)
library(plotly)
library(plyr)
library(flexdashboard)
library("grid")
library("stringr")
library("reshape2")
```
geom_point
=============================================================
Row
-------------------------------------------------------------
### **What is the income pattern among TN counties?**
```{r echo=FALSE}
irs_2011_2015 <- readRDS('./r-objects/irs_2011_2015.rds')
df_sort <- irs_2011_2015 %>%
filter(income_per_tax_return >= 8) %>%
select(county, year, income_per_tax_return)
ggplot(df_sort, aes(x = income_per_tax_return)) + geom_dotplot(dotsize = 1.2) + theme (axis.title=element_text(size=22,face="bold"))
```
### **Is there any change in income over the years?**
```{r irs_2011_2015, echo = FALSE}
df_sort <- irs_2011_2015 %>%
filter(income_per_tax_return >= 8) %>%
select(
county, year, income_per_tax_return
)
ipy <- df_sort %>%
ggplot(
aes(
x = year,
y = income_per_tax_return,
group = county,
color = county
)
) + geom_line(size = .8) +
labs(y = "Income Per Tax Return * 1000", x = "Years") + theme (axis.title=element_text(size=8,face="bold"))
ggplotly(ipy)
```
Row
--------------------------------------------------------------
### **Is there any change in number of tax fiilers across the years?**
```{r}
ggplot_num_returns <- function(df, range, y.label="") {
df_sort_1 <- irs_2011_2015 %>%
dplyr::filter(sum_total_income_returns >= range) %>%
dplyr::select(
county, year, sum_total_income_returns
)
df_sort_1 %>%
ggplot(
aes(
x = year,
y = sum_total_income_returns,
group = county,
color = county
)
) +
geom_line(size = .8) +
labs(y = y.label, x = "") +
theme(axis.text.x = element_text(
face = 'bold',
size = 8
)
) +
theme(axis.text.y = element_text(
face = 'bold',
size = 5
)
) +
theme(axis.title.y = element_text(
size = 8
)
) +
scale_y_continuous(labels = scales::comma) +
scale_color_hue(l = 60, c = 50)
}
ggplotly(ggplot_num_returns(irs_2011_2015, 20000, y.label = "Num of Tax Payers Per Year"))
```
### **Is there any change in number of tax fiilers across the years?**
```{r, echo=FALSE}
ggplotly (ggplot_num_returns(irs_2011_2015, 200000, y.label = "Num of Tax Payers Per Year"))
```
